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Random Walk Based Location Prediction in Wireless Sensor Networks

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Listed:
  • Zhaoyan Jin
  • Dianxi Shi
  • Quanyuan Wu
  • Huining Yan

Abstract

With the development of wireless sensor network (WSN) technologies, WSNs have been applied in many areas. In all WSN technologies, localization is a crucial problem. Traditional localization approaches in WSNs mainly focus on calculating the current location of sensor nodes or mobile objects. In this paper, we study the problem of future location prediction in WSNs. We assume the location histories of mobile objects as a rating matrix and then use a random walk based social recommender algorithm to predict the future locations of mobile objects. Experiments show that the proposed algorithm has better prediction accuracy and can solve the rating matrix sparsity problem more effectively than related works.

Suggested Citation

  • Zhaoyan Jin & Dianxi Shi & Quanyuan Wu & Huining Yan, 2013. "Random Walk Based Location Prediction in Wireless Sensor Networks," International Journal of Distributed Sensor Networks, , vol. 9(12), pages 691042-6910, December.
    • Handle: RePEc:sae:intdis:v:9:y:2013:i:12:p:691042
    DOI: 10.1155/2013/691042
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